{"id":"W2091811399","doi":"10.1186/1297-9686-37-7-601","title":"Power of QTL detection by either fixed or random models in half-sib designs","year":2005,"lang":"en","type":"article","venue":"Genetics Selection Evolution","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Agriculture and Agri-Food Canada; University of Tehran","keywords":"Quantitative trait locus; Statistics; Sire; Inclusive composite interval mapping; Mathematics; Linkage (software); Biology; Regression analysis; Linear regression; Regression; Allele; Genetics; Gene mapping; Animal science; Chromosome","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06896331,0.001433248,0.002261989,0.001586633,0.0003759728,0.001146677,0.002553053,0.001524504,0.003580333],"category_scores_gemma":[0.1245115,0.0013336,0.002809426,0.000869449,0.001560656,0.002720623,0.001566041,0.00112525,0.0006060214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007270278,"about_ca_system_score_gemma":0.001030818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001004742,"about_ca_topic_score_gemma":0.0007054812,"domain_scores_codex":[0.9349656,0.05644898,0.0008352247,0.004667136,0.002577064,0.0005059993],"domain_scores_gemma":[0.8297116,0.1507497,0.004471151,0.01270725,0.001875902,0.0004843623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01393015,0.001102059,0.07647919,0.002053967,0.005523908,0.0004667403,0.00121112,0.4140526,0.03594648,0.04653341,0.0009245293,0.4017758],"study_design_scores_gemma":[0.001214911,0.004249508,0.02771306,0.0001593832,0.001095388,0.0003833121,0.0001038054,0.899856,0.01210463,0.05122957,0.001691395,0.0001990004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.198422,0.0005872353,0.798728,0.00008133054,0.00003970192,0.0002533703,0.0001346374,0.0005497128,0.00120409],"genre_scores_gemma":[0.7973005,0.0003885611,0.1991261,0.0001436425,0.00003058258,0.0009660007,0.000438288,0.0002626973,0.001343637],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06896331,"threshold_uncertainty_score":0.3647172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01488483208045984,"score_gpt":0.224251561568052,"score_spread":0.2093667294875922,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}